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/* NLSF stabilizer:                                         */
/*                                                          */
/* - Moves NLSFs futher apart if they are too close         */
/* - Moves NLSFs away from borders if they are too close    */
/* - High effort to achieve a modification with minimum     */
/*     Euclidean distance to input vector                   */
/* - Output are sorted NLSF coefficients                    */
/*                                                          */
#include "SKP_Silk_SigProc_FIX.h"

/* Constant Definitions */
#define MAX_LOOPS        20

/* NLSF stabilizer, for a single input data vector */
void SKP_Silk_NLSF_stabilize(
          SKP_int    *NLSF_Q15,            /* I/O:  Unstable/stabilized normalized LSF vector in Q15 [L]                    */
    const SKP_int    *NDeltaMin_Q15,       /* I:    Normalized delta min vector in Q15, NDeltaMin_Q15[L] must be >= 1 [L+1] */
    const SKP_int     L                    /* I:    Number of NLSF parameters in the input vector                           */
)
{
    SKP_int        center_freq_Q15, diff_Q15, min_center_Q15, max_center_Q15;
    SKP_int32    min_diff_Q15;
    SKP_int        loops;
    SKP_int        i, I=0, k;

    /* This is necessary to ensure an output within range of a SKP_int16 */
    SKP_assert( NDeltaMin_Q15[L] >= 1 );

    for( loops = 0; loops < MAX_LOOPS; loops++ ) {
        /**************************/
        /* Find smallest distance */
        /**************************/
        /* First element */
        min_diff_Q15 = NLSF_Q15[0] - NDeltaMin_Q15[0];
        I = 0;
        /* Middle elements */
        for( i = 1; i <= L-1; i++ ) {
            diff_Q15 = NLSF_Q15[i] - ( NLSF_Q15[i-1] + NDeltaMin_Q15[i] );
            if( diff_Q15 < min_diff_Q15 ) {
                min_diff_Q15 = diff_Q15;
                I = i;
            }
        }
        /* Last element */
        diff_Q15 = (1<<15) - ( NLSF_Q15[L-1] + NDeltaMin_Q15[L] );
        if( diff_Q15 < min_diff_Q15 ) {
            min_diff_Q15 = diff_Q15;
            I = L;
        }

        /***************************************************/
        /* Now check if the smallest distance non-negative */
        /***************************************************/
        if (min_diff_Q15 >= 0) {
            return;
        }

        if( I == 0 ) {
            /* Move away from lower limit */
            NLSF_Q15[0] = NDeltaMin_Q15[0];
        
        } else if( I == L) {
            /* Move away from higher limit */
            NLSF_Q15[L-1] = (1<<15) - NDeltaMin_Q15[L];
        
        } else {
            /* Find the lower extreme for the location of the current center frequency */ 
            min_center_Q15 = 0;
            for( k = 0; k < I; k++ ) {
                min_center_Q15 += NDeltaMin_Q15[k];
            }
            min_center_Q15 += SKP_RSHIFT( NDeltaMin_Q15[I], 1 );

            /* Find the upper extreme for the location of the current center frequency */
            max_center_Q15 = (1<<15);
            for( k = L; k > I; k-- ) {
                max_center_Q15 -= NDeltaMin_Q15[k];
            }
            max_center_Q15 -= ( NDeltaMin_Q15[I] - SKP_RSHIFT( NDeltaMin_Q15[I], 1 ) );

            /* Move apart, sorted by value, keeping the same center frequency */
            center_freq_Q15 = SKP_LIMIT( SKP_RSHIFT_ROUND( (SKP_int32)NLSF_Q15[I-1] + (SKP_int32)NLSF_Q15[I], 1 ),
                min_center_Q15, max_center_Q15 );
            NLSF_Q15[I-1] = center_freq_Q15 - SKP_RSHIFT( NDeltaMin_Q15[I], 1 );
            NLSF_Q15[I] = NLSF_Q15[I-1] + NDeltaMin_Q15[I];
        }
    }

    /* Safe and simple fall back method, which is less ideal than the above */
    if( loops == MAX_LOOPS )
    {
        /* Insertion sort (fast for already almost sorted arrays):   */
        /* Best case:  O(n)   for an already sorted array            */
        /* Worst case: O(n^2) for an inversely sorted array          */
        SKP_Silk_insertion_sort_increasing_all_values(&NLSF_Q15[0], L);
            
        /* First NLSF should be no less than NDeltaMin[0] */
        NLSF_Q15[0] = SKP_max_int( NLSF_Q15[0], NDeltaMin_Q15[0] );
        
        /* Keep delta_min distance between the NLSFs */
        for( i = 1; i < L; i++ )
            NLSF_Q15[i] = SKP_max_int( NLSF_Q15[i], NLSF_Q15[i-1] + NDeltaMin_Q15[i] );

        /* Last NLSF should be no higher than 1 - NDeltaMin[L] */
        NLSF_Q15[L-1] = SKP_min_int( NLSF_Q15[L-1], (1<<15) - NDeltaMin_Q15[L] );

        /* Keep NDeltaMin distance between the NLSFs */
        for( i = L-2; i >= 0; i-- ) 
            NLSF_Q15[i] = SKP_min_int( NLSF_Q15[i], NLSF_Q15[i+1] - NDeltaMin_Q15[i+1] );
    }
}

/* NLSF stabilizer, over multiple input column data vectors */
void SKP_Silk_NLSF_stabilize_multi(
          SKP_int        *NLSF_Q15,        /* I/O:  Unstable/stabilized normalized LSF vectors in Q15 [LxN]                 */
    const SKP_int        *NDeltaMin_Q15,   /* I:    Normalized delta min vector in Q15, NDeltaMin_Q15[L] must be >= 1 [L+1] */
    const SKP_int         N,               /* I:    Number of input vectors to be stabilized                                */
    const SKP_int         L                /* I:    NLSF vector dimension                                                   */
)
{
    SKP_int n;
    
    /* loop over input data */
    for( n = 0; n < N; n++ ) {
        SKP_Silk_NLSF_stabilize( &NLSF_Q15[n * L], NDeltaMin_Q15, L );
    }
}
